A framework for irrigation performance assessment using WaPOR data: the case of a sugarcane estate in Mozambique

Abstract. The growing competition for finite land and water resources the need to feed an ever-growing population require new techniques monitor performance of irrigation schemes improve productivity. Datasets from FAO's portal Water Productivity through Open access Remotely sensed derived data (WaPOR) are increasingly applied as a cost-effective means support assessment identify possible pathways improvement. This study presents framework that applies WaPOR assess indicators, including uniformity, equity, adequacy, productivity differentiated by method (furrow, sprinkler, centre pivot) at Xinavane sugarcane estate, Mozambique. on water, land, climate in near-real time spatially distributed, with finest spatial resolution area 100 m. were first validated agronomically examining biomass response then used systematically analyse seasonal indicators period 2015 2018 ∼8000 ha. WaPOR-based yield estimates found be comparable estate-measured yields ±20 % difference, root mean square error 19±2.5 t ha−1 absolute 15±1.6 ha−1. A normalization factor enables temporal comparison applied. highlights no single performs best across all indicators. Centre pivot compared sprinkler furrow shows higher but lower three methods have excellent uniformity (∼94 %) four seasons acceptable adequacy most periods season except 2016, when drought was observed. While this is done one scheme, approach can broadened compare other crops fields or Africa diverse management units different agroclimatic zones within FAO coverage. We conclude useful assessing using dataset.